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Secure and Reliable Routing in the Internet of Vehicles Network:AODV-RL with BHA Attack Defense

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 633-659页

作者： Nadeem Ahmed Khalid Mohammadani Ali Kashif Bashir Marwan Omar Angel Jones Fayaz Hassan School of Electronic Science Beijing University of Post and TelecommunicationBeijing100086China department of Computer Science Huanggang Normal UniversityHuanggangChina department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Woxsen School of Business Woxsen UniversityHyderabad502345India department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon information technology and management Illinois Institute of TechnologyChicagoUSA College of Computing Capital Technology UniversityLaurelUSA

Wireless technology is transforming the future of transportation through the development of the Internet of Vehicles(IoV).However,intricate security challenges are intertwinedwith technological progress:Vehicular ad hoc Networks(VANETs),a core component of IoV,face security issues,particularly the Black Hole Attack(BHA).This malicious attack disrupts the seamless flow of data and threatens the network’s overall reliability;also,BHA strategically disrupts communication pathways by dropping data packets from legitimate nodes *** the importance of this challenge,we have introduced a new solution called ad hoc On-Demand Distance Vector-Reputation-based mechanism Local Outlier Factor(AODV-RL).The significance of AODVRL lies in its unique approach:it verifies and confirms the trustworthiness of network components,providing robust protection against *** additional safety layer is established by implementing the Local Outlier Factor(LOF),which detects and addresses abnormal network *** testing of our solution has revealed its remarkable ability to enhance communication in ***,Our experimental results achieve message delivery ratios of up to 94.25%andminimal packet loss ratios of just 0.297%.Based on our experimental results,the proposedmechanismsignificantly improves VANET communication reliability and *** results promise a more secure and dependable future for IoV,capable of transforming transportation safety and efficiency.

关键词： Black hole attack IoV vehicular ad hoc network AODV routing protocol

SIRS epidemic modeling using fractional-ordered differential equations:Role of fear effect

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International Journal of Biomathematics 2024年第5期17卷 79-100页

作者： Shiv Mangal O.P.Misra Joydip Dhar School of Mathematics and Allied Sciences Jiwaji University GwaliorMadhya PradeshIndia department of Mathematics Post Graduate College BinaMadhya PradeshIndia department of Applied Sciences Atal Bihari Vajpayee-Indian Institute of Information Technology and Management GwaliorMadhya PradeshIndia

In this paper,an SIRS epidemic model using Grunwald-Letnikov fractional-order derivative is formulated with the help of a nonlinear system of fractional differential equations to analyze the effects of fear in the population during the outbreak of deadly infectious *** criteria for the spread or extinction of the disease are derived and discussed on the basis of the basic reproduction *** condition for the existence of Hopf bifurcation is discussed considering fractional order as a bifurcation ***,using the Grunwald-Letnikov approximation,the simulation is carried out to confirm the validity of analytic results *** the real data of COVID-19 in India recorded during the second wave from 15 May 2021 to 15 December 2021,we estimate the model parameters and find that the fractional-order model gives the closer forecast of the disease than the classical *** the analytical results and numerical simulations presented in this study suggest different policies for controlling or eradicating many infectious diseases.

关键词： SIRS epidemic model fear effect Mittag-Leffler function Hopf bifurcation parameter estimation

Non-static plane symmetric perfect fluid solutions and Killing symmetries in f(R,T)gravity

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Communications in Theoretical Physics 2024年第2期76卷 145-150页

作者： Preeti Dalal Karanjeet Singh Sachin Kumar department of Mathematics and Statistics Central University of PunjabBathinda151401PunjabIndia department of Mathematics Jaypee University of Information TechnologySolan173234Himachal PradeshIndia

In this paper,the non-static solutions for perfect fluid distribution with plane symmetry in f(R,T)gravitational theory are ***,using the Lie symmetries,symmetry reductions are performed for considered vector fields to reduce the number of independent ***,corresponding to each reduction,exact solutions are *** vectors lead to different conserved ***,we figure out the Killing vector fields corresponding to all derived *** derived solutions are further studied and it is observed that all of the obtained spacetimes,at least admit to the minimal symmetry group which consists of δ_(y),δ_(z) and -zδ_(y)+yδ_(z).The obtained metrics,admit to 3,4,6,and 10,Killing vector *** of linear momentum in the direction of y and z,and angular momentum along the x axis is provided by all derived solutions.

关键词： Einstein field equations perfect fluid solutions f(R T)gravity killing symmetries

Super-resolution diffractive neural network for alloptical direction of arrival estimation beyond diffraction limits

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Light(Science & Applications) 2024年第8期13卷 1602-1614页

作者： Sheng Gao Hang Chen Yichen Wang Zhengyang Duan Haiou Zhang Zhi Sun Yuan Shen Xing Lin department of Electronic Engineering Tsinghua UniversityBeijing 100084China Beijing National Research Center for information Science and technology Tsinghua UniversityBeijing 100084China

Wireless sensing of the wave propagation direction from radio sources lays the foundation for communication,radar,navigation,***,the existing signal processing paradigm for the direction of arrival estimation requires the radio frequency electronic circuit to demodulate and sample the multichannel baseband signals followed by a complicated computing process,which places the fundamental limit on its sensing speed and energy ***,we propose the super-resolution diffractive neural networks(S-DNN)to process electromagnetic(EM)waves directly for the DOA estimation at the speed of *** multilayer meta-structures of S-DNN generate super-oscillatory angular responses in local angular regions that can perform the all-optical DOA estimation with angular resolutions beyond the diffraction *** spatial-temporal multiplexing of passive and reconfigurable S-DNNs is utilized to achieve high-resolution DOA estimation over a wide field of *** S-DNN is validated for the DOA estimation of multiple radio sources over 5 GHz frequency bandwidth with estimation latency over two to four orders of magnitude lower than the state-of-the-art commercial devices in *** results achieve the angular resolution over an order of magnitude,experimentally demonstrated with four times,higher than diffraction-limited *** also apply S-DNN’s edge computing capability,assisted by reconfigurable intelligent surfaces,for extremely low-latency integrated sensing and communication with low power *** work is a significant step towards utilizing photonic computing processors to facilitate various wireless sensing and communication tasks with advantages in both computing paradigms and performance over electronic computing.

关键词： beyond optical network

Advances in neuromorphic computing:Expanding horizons for AI development through novel artificial neurons and in-sensor computing

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Chinese Physics B 2024年第3期33卷 1-23页

作者：杨玉波赵吉哲刘胤洁华夏扬王天睿郑纪元郝智彪熊兵孙长征韩彦军王健李洪涛汪莱罗毅 department of Electronic Engineering Tsinghua UniversityBeijing 100084China Beijing National Research Center for information Science and technology Tsinghua UniversityBeijing 100084China

AI development has brought great success to upgrading the information *** the same time,the large-scale artificial neural network for building AI systems is thirsty for computing power,which is barely satisfied by the conventional computing *** the post-Moore era,the increase in computing power brought about by the size reduction of CMOS in very large-scale integrated circuits(VLSIC)is challenging to meet the growing demand for AI computing *** address the issue,technical approaches like neuromorphic computing attract great attention because of their feature of breaking Von-Neumann architecture,and dealing with AI algorithms much more parallelly and energy *** by the human neural network architecture,neuromorphic computing hardware is brought to life based on novel artificial neurons constructed by new materials or *** it is relatively difficult to deploy a training process in the neuromorphic architecture like spiking neural network(SNN),the development in this field has incubated promising technologies like in-sensor computing,which brings new opportunities for multidisciplinary research,including the field of optoelectronic materials and devices,artificial neural networks,and microelectronics integration *** vision chips based on the architectures could reduce unnecessary data transfer and realize fast and energy-efficient visual cognitive *** paper reviews firstly the architectures and algorithms of SNN,and artificial neuron devices supporting neuromorphic computing,then the recent progress of in-sensor computing vision chips,which all will promote the development of AI.

关键词： neuromorphic computing spiking neural network(SNN) in-sensor computing artificial intelligence

A Non-Parametric Scheme for Identifying Data Characteristic Based on Curve Similarity Matching

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1424-1437页

作者： Quanbo Ge Yang Cheng Hong Li Ziyi Ye Yi Zhu Gang Yao School of Automation Nanjing University of Information Science&TechnologyJiangsu Provincial University Key Laboratory of Big Data Analysis and Intelligent SystemsNanjing University of Information Science&Technologyand the Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)Nanjing University of Information Science&TechnologyNanjing 210044China School of department of Logistics Engineering Shanghai Maritime UniversityShanghai 201306China China Classification Society Nantong Office Nantong 226006China Chinese Flight Test Establishment Xi’an 710089China School of Mathematics Tsinghua UniversityBeijing 100084China School of Automation Nanjing University of Information Science&TechnologyNanjing 210044China department of Logistics Engineering Shanghai Maritime UniversityShanghai 201306China IEEE

For accurately identifying the distribution charac-teristic of Gaussian-like noises in unmanned aerial vehicle(UAV)state estimation,this paper proposes a non-parametric scheme based on curve similarity *** the framework of the pro-posed scheme,a Parzen window(kernel density estimation,KDE)method on sliding window technology is applied for roughly esti-mating the sample probability density,a precise data probability density function(PDF)model is constructed with the least square method on K-fold cross validation,and the testing result based on evaluation method is obtained based on some data characteristic analyses of curve shape,abruptness and *** com-parison simulations with classical methods and UAV flight exper-iment shows that the proposed scheme has higher recognition accuracy than classical methods for some kinds of Gaussian-like data,which provides better reference for the design of Kalman filter(KF)in complex water environment.

关键词： Curve similarity matching Gaussian-like noise non-parametric scheme parzen window.

Proposal for sequential Stern-Gerlach experiment with programmable quantum processors

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Chinese Physics B 2024年第2期33卷 131-136页

作者：胡孟军缪海兴张永生 Beijing Academy of Quantum information Sciences Beijing 100193China State Key Laboratory of Low Dimensional Quantum Physics Department of PhysicsTsinghua UniversityBeijing 100084China Laboratory of Quantum information University of Science and Technology of ChinaHefei 230026China Synergetic Innovation Center of Quantum information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Hefei National Laboratory University of Science and Technology of ChinaHefei 230088China

The historical significance of the Stern–Gerlach(SG)experiment lies in its provision of the initial evidence for space *** time,its sequential form has evolved into an elegant paradigm that effectively illustrates the fundamental principles of quantum *** date,the practical implementation of the sequential SG experiment has not been fully *** this study,we demonstrate the capability of programmable quantum processors to simulate the sequential SG *** specific parametric shallow quantum circuits,which are suitable for the limitations of current noisy quantum hardware,are given to replicate the functionality of SG devices with the ability to perform measurements in different ***,it has been demonstrated that Wigner’s SG interferometer can be readily implemented in our sequential quantum *** the utilization of the identical circuits,it is also feasible to implement Wheeler’s delayed-choice *** propose the utilization of cross-shaped programmable quantum processors to showcase sequential experiments,and the simulation results demonstrate a strong alignment with theoretical *** the rapid advancement of cloud-based quantum computing,such as BAQIS Quafu,it is our belief that the proposed solution is well-suited for deployment on the cloud,allowing for public *** findings not only expand the potential applications of quantum computers,but also contribute to a deeper comprehension of the fundamental principles underlying quantum theory.

关键词： sequential Stern-Gerlach quantum circuit quantum processor

Distributed dynamic task allocation for unmanned aerial vehicle swarm systems:A networked evolutionary game-theoretic approach

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Chinese Journal of Aeronautics 2024年第6期37卷 182-204页

作者： Zhe ZHANG Ju JIANG Haiyan XU Wen-An ZHANG College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China College of Economics and management Nanjing University of Aeronautics and AstronauticsNanjing 211106China College of information Engineering Zhejiang University of TechnologyHangzhou 310023China

Task allocation is a key aspect of Unmanned Aerial Vehicle(UAV)swarm collaborative *** an continuous increase of UAVs’scale and the complexity and uncertainty of tasks,existing methods have poor performance in computing efficiency,robustness,and realtime allocation,and there is a lack of theoretical analysis on the convergence and optimality of the *** paper presents a novel intelligent framework for distributed decision-making based on the evolutionary game theory to address task allocation for a UAV swarm system in uncertain scenarios.A task allocation model is designed with the local utility of an individual and the global utility of the ***,the paper analytically derives a potential function in the networked evolutionary potential game and proves that the optimal solution of the task allocation problem is a pure strategy Nash equilibrium of a finite strategy ***,a PayOff-based Time-Variant Log-linear Learning Algorithm(POTVLLA)is proposed,which includes a novel learning strategy based on payoffs for an individual and a time-dependent Boltzmann *** former aims to reduce the system’s computational burden and enhance the individual’s effectiveness,while the latter can ensure that the POTVLLA converges to the optimal Nash equilibrium with a probability of *** simulation results show that the approach is optimal,robust,scalable,and fast adaptable to environmental changes,even in some realistic situations where some UAVs or tasks are likely to be lost and increased,further validating the effectiveness and superiority of the proposed framework and algorithm.

关键词： Task allocation Unmanned Aerial Vehicles(UAV) Game theory Log-linear learning Distributed optimization algorithm

Ensemble Approach Combining Deep Residual Networks and BiGRU with Attention Mechanism for Classification of Heart Arrhythmias

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Computers, Materials & Continua 2024年第7期80卷 341-359页

作者： Batyrkhan Omarov Meirzhan Baikuvekov Daniyar Sultan Nurzhan Mukazhanov Madina Suleimenova Maigul Zhekambayeva department of information Systems Al-Farabi Kazakh National UniversityAlmaty050040Kazakhstan department of Mathematical and Computer Modeling International Information Technology UniversityAlmaty050040Kazakhstan department of Software Engineering Satbayev UniversityAlmaty050013Kazakhstan

This research introduces an innovative ensemble approach,combining Deep Residual Networks(ResNets)and Bidirectional Gated Recurrent Units(BiGRU),augmented with an Attention Mechanism,for the classification of heart *** escalating prevalence of cardiovascular diseases necessitates advanced diagnostic tools to enhance accuracy and *** model leverages the deep hierarchical feature extraction capabilities of ResNets,which are adept at identifying intricate patterns within electrocardiogram(ECG)data,while BiGRU layers capture the temporal dynamics essential for understanding the sequential nature of ECG *** integration of an Attention Mechanism refines the model’s focus on critical segments of ECG data,ensuring a nuanced analysis that highlights the most informative features for arrhythmia *** on a comprehensive dataset of 12-lead ECG recordings,our ensemble model demonstrates superior performance in distinguishing between various types of arrhythmias,with an accuracy of 98.4%,a precision of 98.1%,a recall of 98%,and an F-score of 98%.This novel combination of convolutional and recurrent neural networks,supplemented by attention-driven mechanisms,advances automated ECG analysis,contributing significantly to healthcare’s machine learning applications and presenting a step forward in developing non-invasive,efficient,and reliable tools for early diagnosis and management of heart diseases.

关键词： CNN BiGRU ensemble deep learning ECG arrhythmia heart disease